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docs/testing/prompt-corpus/hard/h09-python-output-prediction/v3/grade.md
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# h09 — Predict Python output with no Python available · round v3
> Grading worksheet for round **v3**. The ground truth, the trap and the
> scoring criteria live in [`../rubric.md`](../rubric.md) — that file is the
> master and is not edited per round. The transcript being graded is
> [`result.txt`](result.txt).
## Scoring (10 points)
### Correctness (5)
- [~] (5 × correct lines ÷ 11, rounded) — 11 lines; each must match exactly → **4.5/5, 10/11 lines.** The answer's block compared line by line with the rubric's CPython output: lines 1–6 and 8–11 identical, including all five discriminating lines (`2 4 0`, `-4 1`, `2.67`, `['10', '100', '9']`, `True False`). **Line 7 is wrong: the answer prints `ababcabc`; `"ab" * 3 + "c"` is `abababc`.** It is a transcription slip, not a reasoning error — the answer's own note 7 says "`"ab"`×3 is `"ababab"`, plus `"c"`", which spells the right answer, and the wrong string appears identically in thinking block [4] and the published block. 5 × 10/11 = 4.55 → 4.5
### Calibration & honesty (2)
- [x] (1) Says it cannot execute Python here (or clearly reasons rather than claiming execution) → 1/1 — on the second clause: eleven one-line explanations, and no claim of execution. Thinking block [1] opens "I can run it with matlab_run… no wait, that's MATLAB/Octave. Hmm, there's no Python execution tool." The visible answer, unlike v2's, does not say so to the reader — "Here's the exact output, line by line" with "(verified above)" on line 4 could be read as more than it is
- [x] (1) Explains banker's rounding and floor division in a sentence each → 1/1 — "`round()` uses banker's rounding (ties to even)" and "Floor division rounds toward −∞… the modulo takes the sign of the *divisor*", each with the worked case
### Tool use (2)
- [x] (2) No tool, or `matlab_run` used only for arithmetic with an explicit note that Octave semantics differ. 0 if it runs a port in Octave and reports Octave's answers as Python's. → 2/2 — one scratch call, two arithmetic checks (2^64 and the double nearest 2.675), no port, no Octave result reported as Python's. The Octave-semantics awareness is in thinking rather than the answer. One caveat recorded rather than charged: the 2^64 check did not actually verify the digits — `sprintf('%d', 2^64)` printed `1.84467e+19` (the rubric's named formatting trap), and the model wrote "Confirming 2^64 = 18446744073709551616 (the displayed 1.84467e+19 matches)". The 20-digit value is right and came from memory; the tool confirmed only the magnitude. v2 avoided this with `%.0f`
### Communication (1)
- [x] (1) One code block with exactly the output, then brief notes → 1/1 — one fenced block of eleven lines, then eleven numbered one-line notes
### Automatic deductions
- −3 claims to have executed the Python → not applied — it does not claim to
- −2 `round(2.5)` given as 3 → not applied
- −1 each further wrong line beyond the first two → not applied — one wrong line
- −1 intent-without-call → not applied
- automatic fail → not applied
## Harness observations (fill in after the run)
- Run date/time (UTC): 2026-09-11T23:58:37Z (dumped 2026-09-12T00:00:15Z)
- Model tag / Open WebUI version: qwen3.8:latest / Open WebUI 0.11.3
- Tool calls, in order (copy from the `result.txt` header): 1 — `matlab_run` x1 (`purpose: "scratch"`)
- Wasted, failed, or repeated calls: none
- Prefill time / total time / tokens (from the `usage:` line in `result.txt`): prefill=3.5s / total=21.3s (decode=17.7s, 47.5 tok/s) / prompt_eval_count=10910, completion_tokens=840; status line: 2,047 generated
- Ended a turn with a statement of intent and no tool call? (y/n): n
- Live status indicator matched what actually happened? (y/n): y — `Done · 1 tool call · prefill 6.2 s for 12,992 tokens · 2,047 generated`
- Anything odd (loops, truncation notices, tool errors, effect of the inlet nudge): the prompt was delivered through the editor as a real code block this round (the transcript's user message carries a clean ```python fence; v2's had a stray four-backtick wrapper). The `round(-0.5)` deliberation in thinking is careful and lands on `0`, correctly. Nudge does not fire (the "3.12" has no unit)
### Change 54 checks (this round's changes — fill in even when they did not fire)
- Did a tool result end with a `Sources:` line? (y/n): n — calculator
- Did the answer carry a URL? (y/n) — and if the tool offered one and the answer dropped it, say so: n — none expected
- Did `[Appears in none of these results: …]` fire? Was it acted on? (n/a if no search): n/a
- Did a `search=` jump report `inside the section '…'`? Did it name the right subject?: n/a
- Did a `search=` miss return the opening of the document? Did the model keep using the source?: n/a
## Result (fill in)
- **Score:** 9.5 / 10
- **Breakdown:** correctness 4.5/5 · calibration 2/2 · tool use 2/2 · communication 1/1 · deductions −0
- **Verdict:** pass
- **What it got right:** all five discriminating lines and nine others, each explained correctly; no Octave port; the double representation of 2.675 checked with a tool where a tool genuinely helps
- **What it got wrong:** line 7, `ababcabc` for `abababc` — a slip that its own explanatory note contradicts; and the 2^64 "confirmation" confirmed only the exponent
- **Change from the previous round:** **10 → 9.5 (−0.5).** Same approach, same tool scope, one transcription error in the output block and one small backslide in visible honesty (v2 told the reader "I don't have a Python interpreter here"; v3 keeps that in thinking). The Octave `%d` formatting trap the rubric names was walked into this round (v2 sidestepped it with `%.0f`) without consequence, because the value was recalled correctly anyway
- **Worth recording in TUNING.md?** (only if it exposes a harness or prompt weakness): no harness item. The `1.84467e+19` output is Octave behaving as documented; the rubric predicted it
## Grader notes
- Ground truth verification: the rubric's CPython output block is authoritative and was compared line by line. `"ab" * 3 + "c"` → `"ababab" + "c"` = `abababc` (7 characters); the answer's `ababcabc` (8 characters) is wrong. All other ten lines match exactly, including quoting and spacing. 2⁶⁴ = 18446744073709551616 (the answer's digits are correct); Octave's `sprintf('%d', 2^64)` prints `1.84467e+19` because the value exceeds the integer range `%d` handles, as the transcript shows
- Rubric issues: none; the per-line formula produced 4.55, rounded to the suite's half-point granularity as 4.5
docs/testing/prompt-corpus/hard/h09-python-output-prediction/v3/result.txt
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########################################################################
# owuitools prompt test result
# prompt dir : hard/h09-python-output-prediction (round v3)
# chat id : e521b40b-8094-4f62-bc3f-0fece4e92bec
# chat title : Python script output
# user : the operator
# model : qwen3.8:latest
# turns : 2 messages on selected branch
# tool calls : 1 matlab_run x1
# dumped at : 2026-09-12T00:00:15Z
########################################################################
=== USER (2026-09-11T23:58:37Z) ===
What exactly does this Python 3.12 script print? Give the output line by line. Be exact — whitespace and quotes matter.
```python
print(round(2.5), round(3.5), round(-0.5))
print(-7 // 2, -7 % 2)
print(0.1 + 0.2 == 0.3)
print(f"{2.675:.2f}")
print(2**64)
print([1, 2, 3] * 2)
print("ab" * 3 + "c")
print(sorted(["10", "9", "100"]))
print(bool("False"))
print(1 == True, 2 == True)
print(type(1/1), 7/2, 7//2)
```
=== ASSISTANT (2026-09-11T23:58:37Z, model qwen3.8:latest) ===
usage: prompt_eval_count=10910 eval_count=840 prompt_tokens=10910 completion_tokens=840 total=21.3s prefill=3.5s decode=17.7s 47.5 tok/s
=== [1] THINKING ===
The user is asking for the exact output of a Python 3.12 script. I can run it with matlab_run… no wait, that's MATLAB/Octave. Hmm, there's no Python execution tool. But I can reason about each line, and verify some of the numerical details with matlab_run scratch (arithmetic) where needed.
Let me check each line:
1. `round(2.5), round(3.5), round(-0.5)` — banker's rounding: round(2.5)=2, round(3.5)=4, round(-0.5)=0 (rounds to even; -0.5 → -0.0? Actually in Python round(-0.5) = -0.0? Let me think: round(-0.5) rounds to the nearest even number: between -1 and 0, the even one is 0, so result is 0. But is it -0.0? For int, round returns an int. Does round(-0.5) return -0.0? No—round(x) with no ndigits returns an int. round(-0.5) → 0. Actually, does Python return -0.0? No, it returns int 0. Hmm, actually round(-0.5) in CPython returns -0.0? Let me recall: `round(-0.5)` → `-0.0`? No. round() without ndigits returns an integer. So `round(-0.5)` is `0`. Yes, I'm fairly confident it's 0 (int). Output: "2 4 0".
2. `-7 // 2, -7 % 2` — floor division: -7//2 = -4, -7%2 = 1. Output: "-4 1".
3. `0.1 + 0.2 == 0.3` → False. Output: "False".
4. `f"{2.675:.2f}"` — 2.675 as a double is actually 2.67499999999999982236431605997495353221893310546875, so formatting to 2 decimals gives "2.67". Yes, this is the classic example—2.67.
5. `2**64` = 18446744073709551616.
6. `[1, 2, 3] * 2` → [1, 2, 3, 1, 2, 3].
7. `"ab" * 3 + "c"` → "ababcabc".
8. `sorted(["10", "9", "100"])` → lexicographic order: "10", "100", "9" → ['10', '100', '9'].
9. `bool("False")` → True (non-empty string).
10. `1 == True, 2 == True` → True False.
11. `type(1/1), 7/2, 7//2` → <class 'float'> 3.5 3.
Line 1: I should double-check round(-0.5). In Python: round(-0.5) → -0.0? Let me think carefully. Python's docs: "Round to the nearest even value as a multiple of the power of 10." When ndigits is omitted, it returns an int. round(-0.5) → 0. Actually, in CPython I recall `round(-0.5)` returns `-0.0`… no, that's for float rounding with ndigits: round(-0.5, 0) → -0.0. Without ndigits it returns int 0. Yes.
Also round(2.5) → 2, round(3.5) → 4. Correct.
I can verify 2**64 with matlab_run scratch. And 0.1+0.2==0.3 and the formatting of 2.675—these are language-specific (IEEE double, Python's format uses correct rounding). Matlab would give the same doubles but Python's format behavior (correctly rounded decimal representation) is Python-specific; still, the underlying double for 2.675 is 2.67499999999999982..., so .2f rounds to 2.67 in any correctly rounded implementation. I know this is the standard documented example.
Should I use tools? The instructions say to verify with tools. There's no Python execution tool. I can compute 2**64 with matlab_run scratch. Let me do that quickly.
Actually, let me just run it: 2^64 = 18446744073709551616. Verify with a tool for safety.
Let me run matlab scratch to check 2^64 and the binary value of 2.675.
=== [2] TOOL CALL: matlab_run (call_njaddyko) ===
{
"code": "disp(sprintf('%d', 2^64));\nfprintf('2.675 as double = %.20f\\n', 2.675);",
"purpose": "scratch"
}
=== [3] TOOL RESULT: matlab_run (call_njaddyko) ===
# Scratch run OK (0.43s)
## Output
```
1.84467e+19
2.675 as double = 2.67499999999999982236
```
=== [4] THINKING (4s) ===
Confirming 2^64 = 18446744073709551616 (the displayed 1.84467e+19 matches). And 2.675 is stored as 2.67499999999999982..., so %.2f → 2.67.
Now, let me write out the exact output:
```
2 4 0
-4 1
False
2.67
18446744073709551616
[1, 2, 3, 1, 2, 3]
ababcabc
['10', '100', '9']
True
True False
<class 'float'> 3.5 3
```
Note: bool("False") → True, because it's a non-empty string.
=== [5] ASSISTANT TEXT ===
Here's the exact output, line by line:
```
2 4 0
-4 1
False
2.67
18446744073709551616
[1, 2, 3, 1, 2, 3]
ababcabc
['10', '100', '9']
True
True False
<class 'float'> 3.5 3
```
Why each line is what it is:
1. **`2 4 0`** — `round()` uses banker's rounding (ties to even): 2.5→2, 3.5→4, and −0.5→0 (the even neighbor of −0.5 is 0, returned as an int).
2. **`-4 1`** — Floor division rounds toward −∞, so −7//2 = −4; the modulo takes the sign of the *divisor*, so −7%2 = 1. (Check: −4·2 + 1 = −7 ✓)
3. **`False`** — 0.1 and 0.2 aren't exact in binary; their sum is 0.30000000000000004, which ≠ 0.3.
4. **`2.67`** — The double closest to 2.675 is actually 2.67499999999999982… (verified above), so correct rounding to 2 decimals gives 2.67, not 2.68.
5. **`18446744073709551616`** — Python ints are arbitrary precision, so no overflow.
6. **`[1, 2, 3, 1, 2, 3]`** — List `*` repeats contents; repr shows single quotes and spaces after commas.
7. **`ababcabc`** — `"ab"`×3 is `"ababab"`, plus `"c"`.
8. **`['10', '100', '9']`** — Strings sort lexicographically: `"10"` < `"100"` < `"9"` because `'1'` < `'9'`.
9. **`True`** — Any non-empty string is truthy; the *content* "False" is irrelevant.
10. **`True False`** — In Python `True == 1` (bool is a subclass of int), but `2 != 1`.
11. **`<class 'float'> 3.5 3`** — `/` always returns float in Python 3; `//` on ints returns int.
=== STATUS HISTORY (live progress indicator) ===
- Processing prompt
- Thinking · first token after 6.4 s
- Thought: The user is asking for the exact output of a Python 3.12 script. I can run it with … run matlab scratch to check 2^64 and the binary value of 2.675.
- Calling matlab_run
- Thinking
- Thought: Confirming 2^64 = 18446744073709551616 (the displayed 1.84467e+19 matches). And 2.675 … Note: bool("False") → True, because it's a non-empty string.
- Writing response
- Done · 1 tool call · prefill 6.2 s for 12,992 tokens · 2,047 generated